Ned Moorfield’s Post

23 questions that will help organize hypotheses, ideas and features in a roadmap: – At what stage of the user life cycle does this solution appear? – How would we characterize the problem area of this solution? – What is the main benefit of the solution for users? – What extras? What opportunities does this solution open to the product/users? – How specific is this solution? – Does this solution solve the problem more or expand the possibilities? – Is this a gradual change or gradual improvement? – How quickly will users notice this solution? – What is the expected “blast radius” of this solution? – What data and metrics will circulate in such a solution? – How does this decision affect business metrics? – What is the main risk of this decision for business? – What is the main risk of this solution for users? – What is the main risk if we decide NOT to work on this solution? – Do your competitors have similar solutions? – How does our solution differ from competitors’ solutions? – How different is our new solution from our current solutions? – How is this solution related to other solutions within the product? – What current priorities in the roadmap does this decision shift? – What level of development and support will be required for this solution? – What organic and artificial limitations does this solution have? – What research was carried out when modeling the solution? – How comfortable are we if we fail with such a decision? – How reversible is this solution? – If we had to describe this decision as a Game, how would we describe it? #roadmap #productmanager #productmanagement #productowner #planning #projectmanagement #timemanagement #ai #artificialintelligence #future #technologies #planner

Trust your peers and assume good intent. I’ve seen that growth comes with a mindset where you don’t just jump to conclusions and start blaming people if some product decisions don’t go your way, even when you’ve expressed your opinion and made a good persistent case for it. Instead, you trust your peers are smart (just like you are), had good insights and intent behind making a decision, trust that the decision that was made is going to land your product and team in a better place and fully support it. If it goes wrong, you could try your approach that you pitched on the first place and now you’d have more data to support it along with well aligned peers who’d have your back. This has worked for me multiple times in the past. The caveat is, data wins arguments. But in your product journey, you’d find multiple instances where you’d not have enough data or enough time to get the data to develop a data backed hypotheses. That is when this approach would work. #productmanagement #career #data #tech #AI #growth

I came across this recent conversation with a few colleagues who were joking that AI is going to take over Product manager jobs, so got me wondering. In the contemporary dynamic of technological advancement, artificial intelligence (AI) has emerged as an indispensable asset for businesses striving for operational efficiency and innovative prowess. Nonetheless, despite its considerable capabilities, AI encounters limitations, notably in domains necessitating empathy, intuition, and intricate decision-making. Innovation and Ingenuity: While AI adeptly processes data and furnishes insights, it struggles to transcend conventional frameworks and conceive genuinely innovative solutions. Human product managers inject creativity into the equation, envisaging novel features, functionalities, and product trajectories that resonate with users and confer competitive distinction upon the product. Strategic Decision-Making: AI excels in data assimilation and pattern recognition, yet it lacks the intuitive acumen and strategic foresight inherent in human product managers. These professionals adeptly navigate intricate market dynamics, discern priority initiatives, and formulate decisions by amalgamating data-centric analysis with contextual comprehension. Adaptability and Versatility: In an environment characterized by perpetual flux in market trends and user preferences, human product managers excel in swift adaptation and strategic recalibration. They pivot expediently in response to evolving circumstances, harnessing their experiential reservoirs and discernment to steer the product towards triumph. Human Product Manager Vs AI: Understanding User Requisites: Human product managers excel in conducting comprehensive user research, soliciting feedback, and deciphering nuanced insights to inform product development strategies. Cultivating Relationships: The cultivation of trust and rapport with customers, stakeholders, and cross-functional teams necessitates human connection and adept interpersonal skills. Fostering Innovation: Human product managers leverage their creativity and industry acumen to discern nascent trends, explore uncharted opportunities, and catalyze product innovation. Strategic Pioneering: The crafting of a forward-looking vision for the product, its alignment with corporate objectives, and the adaptive refinement of strategies contingent upon market dynamics demand human discernment and strategic acumen. Stakeholder Management: The negotiation of competing priorities, resolution of conflicts, and alignment of divergent stakeholder interests mandate human diplomacy and communication prowess. In conclusion, while AI can augment certain facets of product management by automating repetitive functions and furnishing data-driven insights, it cannot supplant the nuanced discernment, empathetic engagement, and creative ingenuity that human product managers embody. #Product #productmanagment #AI #AIProductManager

As Theodore Roosevelt once said, "Dare mighty things." This resonates deeply with the role of a product manager, especially in today’s fast-paced, AI-driven world. Our job is not just to maintain the status quo but to venture into uncharted territories, pushing the boundaries of innovation and user experience. In the age of AI, the stakes are higher, and the challenges are more complex. We are tasked with integrating cutting-edge technology while balancing ethical considerations and ensuring that our products serve diverse and inclusive user bases. It’s a delicate dance between ambition and responsibility. Here’s my take: The future of product management will hinge more on our ability to understand and leverage AI than on traditional project management skills. As AI continues to evolve, so too must our strategies, mindsets, and tools. To my fellow product fellows, coders, and designers: How are you daring mighty things in your projects? Do you agree that AI will be the defining factor of our success in the coming years, or do you believe traditional skills will remain paramount? Share your thoughts below—I’m eager to hear your perspectives! 🤖🚀 #ProductManagement #AI #Innovation #DareMightyThings #TechLeadership

AI is the talk of the town these days! It’s constantly changing the face of all industries.  Let’s chat about the dynamic shift happening in Product Management, especially with the transformative embrace of AI in the tech landscape. In my journey navigating the tech spheres, I've witnessed the winds of change, and 2024 is shaping up to be the year where AI takes the reins of Product Management: 🧠 AI as the Navigator: Say goodbye to the guesswork! AI is becoming the trusted guide in decision-making. It's not about replacing human intuition but amplifying it with data-driven insights. 🤯💡 🌐 Global Collaboration: As our world becomes more interconnected, so does our approach to Product Management. AI facilitates seamless collaboration across borders, time zones, and diverse teams. 🌍🤝 💻 Personal Touch in Automation: Contrary to common belief, AI isn't stripping away the personal touch. Instead, it's refining processes, allowing more room for creativity and strategic thinking. 🎨🔄 📊 Data, the True North: AI thrives on data, and in Product Management, it's a gold mine. Harnessing the power of AI-driven analytics unlocks deeper insights into user behavior and market trends. 📈📊 🚀 Agile Evolution: With AI in the driver's seat, the Agile approach takes on a new dimension. Rapid iteration fueled by AI insights ensures that products evolve in tune with ever-changing demands. 🔄🚀 💬 Join the Dialogue: How has AI impacted your Product Management journey? Any exciting stories or challenges? Let's share insights! 💬 #AIinProductManagement #TechInnovation #FutureOfWork #DigitalTransformation #90dayslinkedIn As we ride the wave of AI integration, the synergy between human ingenuity and artificial intelligence is where the magic happens. 🤖✨ Exciting times lie ahead, and I can't wait to hear your thoughts on this transformative journey! 🌟

🤖 Embarking on the Machine Learning Journey: Guiding First-Timers to Success 🤖 The leap into Machine Learning (ML) is more than adopting a new technology; it’s embracing a fundamental shift in operational paradigms. For organizations taking their inaugural steps into ML, the journey is exhilarating, albeit replete with hurdles. Here’s how to shepherd those at the starting line: ✨ Cultivate Understanding: ML isn’t a magic wand; it’s a strategic enhancer. Begin by demystifying ML - educate teams not just on its functionality, but its practical implications and limitations. Foster a culture where curiosity leads to learning and skepticism breeds questions, not barriers. 🎯 Identify the Right Problems: The most sophisticated ML models are futile if applied to the wrong problems. Start with issues that are well-defined, data-dependent, and impactful. Quick wins are crucial; they demonstrate value, building momentum and support for more complex initiatives. 📊 Data Quality Over Quantity: ML thrives on data, but the focus should be on quality, not quantity. Ensure your data is relevant, clean, and bias-minimized. Establish robust data governance practices early, setting the stage for scalable, sustainable ML endeavors. 👥 Cross-functional Collaboration: ML’s success is a team sport. Establish interdisciplinary task forces combining IT, data scientists, and business stakeholders. Encourage open dialogue to align goals, set realistic expectations, and foster collective ownership of the ML journey. 🔄 Embrace Iteration: ML is not a set-it-and-forget-it solution. It’s iterative and evolving. Cultivate resilience in the face of setbacks. Learn from models that misfire, recalibrate, and leverage those insights to refine future efforts. 🌱 Seek External Expertise: Partnering with seasoned experts can significantly shorten the learning curve. Whether through consultancy or collaborative projects, external input can provide fresh perspectives, mentorship, and nuanced strategies drawn from diverse experiences. Launching ML initiatives can be a daunting odyssey, especially for newcomers. However, with grounded expectations, strategic problem selection, and an iterative mindset, the journey can lead to transformative outcomes. Remember, the first step into ML isn’t about immediate perfection; it’s about progressive learning and long-term innovation. #MachineLearning #DigitalTransformation #Innovation #DataQuality #Collaboration Adjustments or personal insights can be added to personalize your post further!

Time is running out to get certified as a Data and AI Product Manager. Demand for talent is high because Data and AI Product Managers solve high-value problems. ✅ The Data Team Cannot Demonstrate ROI Or Is Seen As A Cost Center ✅ ‘Proof Of Concept Purgatory’ With Very Little Making It Beyond Evaluation ✅ A Lack Of Prioritization, Constant Interruptions From Fire Drills, & Every Request Is Priority 1 ✅ C-level Leaders & The Business Aren’t Interested Or Engaged ✅ Low Adoption Rates For Data & AI Products ✅ The Business Is Afraid Of Change And Sees AI As A Threat ✅ No One Listens: The Best Ideas Are Ignored Or Overlooked There are only a few spots left. Take a look at the outline and click the link under my name to learn more.

🤖 Will AI and bots ever fully replace the indomitable role of Product Managers in the tech realm? 🚀 Amidst the ever-evolving discourse surrounding AI's potential to reshape job landscapes, one fact remains unwavering: the essence of Product Managers defies easy automation. 🎯 Crafted Strategy, Powered by Humans: Product Managers seamlessly weave market research, product strategy, and customer insights into a unified vision. Their decisions are informed by a profound grasp of both target audiences and competitive dynamics – a synergy that technology struggles to replicate. 🧠 The Human Creative Spark: While AI excels in data analysis, the quintessential art of creative decision-making belongs uniquely to humans. The ability to spot opportunities, innovate, and visualize uncharted product realms requires a spark of creativity that algorithms can't ignite. 🤝 Collaborators Extraordinaire: At the intersection of departments, Product Managers are maestros of collaboration. Their adept interpersonal skills harmonize diverse teams, fostering communication among designers, engineers, sales, and executives, all working toward shared goals. As we tread the path of tech advancement, the role of Product Managers stands resolute, a testament to the enduring importance of human insight, ingenuity, and leadership. 💬 What's your take? Join the conversation and share your thoughts on the future of Product Management in a tech-driven world. #ProductManagement #TechInnovation #HumanExpertise #AIandJobs #JoinTheConversation #LogicLoom

I had fun sharing learnings about my #work journey. Someone asked me, "Remi how do you pick what topics to speak on?" Simple! Things I wish someone else told me when I was just starting off my career. Talk Highlights: 1️⃣ Own the Value: Become a product owner, not just a participant. 2️⃣ Early Influence: The sooner you're in the deal, the bigger the impact. 3️⃣ Data-Driven: Making informed decisions is no longer optional. 4️⃣ AI Integration: Disrupt or get disrupted. 🎥 Check it out the full-length presentation here - https://lnkd.in/djqxrkfe #PublicSpeakingJourney #OwnYourValue #DataDrivenDecisions #CareerInsights #LeadershipTalks

Find this post from Sriram Natarajan to be very insightful.